For both cost and environmental reasons, consumers (be they individuals, businesses, etc.) are under increasing pressure to reduce the consumption of utilities such as electricity, water and gas. Methods of so-called non-intrusive load monitoring (NILM) have been developed, which involve measuring a level of consumption of a utility by a site and then identifying which particular appliances are consuming the utility at any point in time.
The majority of NILM solutions use techniques known as “event-based” techniques. In these techniques, a utility consumption profile of the site is recorded and analysed to look for significant changes in the state of utility consumption by the site (caused, for example, by devices at the site being turned on or off). FIG. 1 of the accompanying drawings shows a typical utility consumption profile for a domestic site. In such a utility consumption profile, changes in the utility consumption of the site can be seen and the devices which are causing the change in utility consumption may be inferred using heuristic algorithms. Examples of using event-based techniques in NILM can be seen in: Hart, G. W., “Nonintrusive appliance load monitoring”, Proceedings of the IEEE, 80, 1870-1891; and in U.S. Pat. No. 4,858,141 and U.S. Pat. No. 5,483,153.
While event-based techniques can provide reasonable results in some circumstances, they suffer from a number of significant limitations. Firstly, to calculate the magnitude of utility consumption by a device, it is necessary to sample the utility consumption profile at points which are either side of the change in state of the device. Hence the accuracy of this technique is limited by the noise in the utility consumption profile.
Secondly, for situations where multiple devices are changing state simultaneously or where multiple devices are changing state in quick succession, the profile indicating a change of state of an individual device may be obscured or distorted by a change in the state of one or more other devices. This may happen at a commercial site, for example. FIG. 2 of the accompanying drawings shows a utility consumption profile which has been recorded at a factory. In a situation such as this, where a large number of devices are installed and many devices are changing state simultaneously or in quick succession, the utility consumption profile is too complicated for event-based techniques to successfully analyse.
It would therefore be desirable to provide an improved method of non-intrusive load monitoring.